Design and Simulation of a Nanoscale Threshold-Logic Multiplier

Multiplication is one of the most important operations in microprocessors and digital signal processing systems. Different multiplier architectures have been proposed in the literature. One of the most widely used architecture is the Wallace tree multiplier. This multiplier is known for its high speed. However, it occupies a large area. In this paper, we used Threshold Logic Gates instead of conventional logic gates to reduce the area. The multiplier was designed in 65nm CMOS technology, and achieved 28% reduction in the number of transistors compared to the one with conventional logic gates. It also achieved a lower power-delay-product

The evolving SARS-CoV-2 epidemic in Africa: Insights from rapidly expanding genomic surveillance

INTRODUCTION Investment in Africa over the past year with regard to severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) sequencing has led to a massive increase in the number of sequences, which, to date, exceeds 100,000 sequences generated to track the pandemic on the continent. These sequences have profoundly affected how public health officials in Africa have navigated the COVID-19 pandemic. RATIONALE We demonstrate how the first 100,000 SARS-CoV-2 sequences from Africa have helped monitor the epidemic on the continent, how genomic surveillance expanded over the course of the pandemic, and how we adapted our sequencing methods to deal with an evolving virus. Finally, we also examine how viral lineages have spread across the continent in a phylogeographic framework to gain insights into the underlying temporal and spatial transmission dynamics for several variants of concern (VOCs). RESULTS Our results indicate that the number of countries in Africa that can sequence the virus within their own borders is growing and that this is coupled with a shorter turnaround time from the time of sampling to sequence submission. Ongoing evolution necessitated the continual updating of primer sets, and, as a result, eight primer sets were designed in tandem with viral evolution and used to ensure effective sequencing of the virus. The pandemic unfolded through multiple waves of infection that were each driven by distinct genetic lineages, with B.1-like ancestral strains associated with the first pandemic wave of infections in 2020. Successive waves on the continent were fueled by different VOCs, with Alpha and Beta cocirculating in distinct spatial patterns during the second wave and Delta and Omicron affecting the whole continent during the third and fourth waves, respectively. Phylogeographic reconstruction points toward distinct differences in viral importation and exportation patterns associated with the Alpha, Beta, Delta, and Omicron variants and subvariants, when considering both Africa versus the rest of the world and viral dissemination within the continent. Our epidemiological and phylogenetic inferences therefore underscore the heterogeneous nature of the pandemic on the continent and highlight key insights and challenges, for instance, recognizing the limitations of low testing proportions. We also highlight the early warning capacity that genomic surveillance in Africa has had for the rest of the world with the detection of new lineages and variants, the most recent being the characterization of various Omicron subvariants. CONCLUSION Sustained investment for diagnostics and genomic surveillance in Africa is needed as the virus continues to evolve. This is important not only to help combat SARS-CoV-2 on the continent but also because it can be used as a platform to help address the many emerging and reemerging infectious disease threats in Africa. In particular, capacity building for local sequencing within countries or within the continent should be prioritized because this is generally associated with shorter turnaround times, providing the most benefit to local public health authorities tasked with pandemic response and mitigation and allowing for the fastest reaction to localized outbreaks. These investments are crucial for pandemic preparedness and response and will serve the health of the continent well into the 21st century

Re-urbanizing Ismailia : by implementing an urban infill housing strategy

Thesis: S.M., Massachusetts Institute of Technology, Department of Architecture, 2014.Cataloged from PDF version of thesis.Includes bibliographical references (pages 76-77).Ismailia is a modem Egyptian city located midway along the Suez Canal, the renowned waterway linking the Red Sea to the Mediterranean Sea. The city was developed in 1983 following a French archetype, in collaboration with the French, who were in charge of the operation of the Suez Canal, to serve as the headquarters of the Suez Canal Authority and to house its mainly French and European staff. During the ensuing years, Ismailia remained compact and respected a dense and well-organized urban fabric, following its original plan. However, the city was evacuated in 1967 for six years during the Arab-Israeli war (1948-1973). It was in the latter half of the twentieth century, that Ismailia was re-planned and re-inhabited but with many undefined spaces between and within neighborhoods and that didn't have any clear identity. These neighborhoods lie within a district called Al- Sheikh Zayed, which occupies the whole eastern half of Ismailia. Rather than develop existing vacant plots in the district, the government plans to expand outside the city peripheries towards the desert, essentially creating an extensive, unsustainable urban sprawl. This thesis proposes an alternative plan that creates a legible structure and a recognizable identity within one neighborhood at the heart of the Sheikh Zayed district. Using an urban infill strategy, this proposed plan is based on the premise that compact cities are more sustainable because dense areas share the same infrastructure and public services, are more walkable and bikable, and therefore they save energy and reduce pollution. Through site analysis, I identify an optimal solution for this district that can serve as a model development within Ismailia and can be applied in underdeveloped urban areas within other Egyptian cities. Through my design I introduce a better programming for the neighborhood, provision adequate street network and public and green spaces. The outcome of the thesis is then an urban design proposal for the Sheikh Zayed neighborhood with a block design and a general landscape scheme.by Mariam Raafat Abdel Azim.S.M

Is there an added role for diffusion weighted imaging in the staging of cervical carcinoma?

Objective: To assess the diagnostic accuracy of diffusion weighted imaging (DWI-MRI) being a non-contrast based MR sequence versus dynamic contrast enhanced MRI (DCE-MRI) in the preoperative loco-regional staging of the cervical carcinoma. Methodology: Fifty cases of proved cancer cervix prior staging subjected to dynamic post contrast technique: one pre-and six post contrast phases (40 s each). DWI was scanned using different b values and ADC values were measured. Results: DWI was the most accurate in staging operable cases (93.3%).Parametrial infiltration was overestimated in 3 cases versus 4 cases in DCE-MR. DWI showed 100% sensitivity, positive predictive value and accuracy in the assessment of locally advanced carcinomas. In metastatic lymph nodes, DCE-MR showed the least accuracy of 86%. Conclusion: DWI is helpful in discriminating local from locally advanced cervical carcinomas. DCE-MR can delineate cervical carcinomas confined to the uterus and exclude bladder/rectal invasion

Diffusion-weighted magnetic resonance imaging in the assessment of ovarian masses with suspicious features: Strengths and challen

Objective: To evaluate diagnostic performance of diffusion weighted imaging (DWI) in evaluating ovarian masses with suspicious features on magnetic resonance imaging (MRI). Patients and methods: Pelvic MRI and DWI assessed 235 complex and solid ovarian masses of suspicious MRI features. On DWI, scanning acquired by b values: 0, 500, 1000 and 1500. Analysis considered signal intensity (SI) at b1000 and the mean ADC values for the solid components of the masses. Results: Included masses proved benign in 75(32%), borderline (low potential malignancy) in 55(23.4%) and malignant in 105(44.6%). Restricted diffusion was observed in all of the invasive malignancy (57.1%, n = 105/184). Benign and borderline tumors with high DWI SI presented 15.2% and 27.7% respectively (P < 0.05). The mean ADC value was 1.2 + 0.34 × 10−3 mm2/s, 1.1 + 0.06 × 10−3 mm2/s, and 0.83 + 0.15 × 10−3 mm2/s for benign, borderline and malignant masses respectively. The ADC values of malignant masses and benign masses with fibrous components showed no significant difference (P = 0.333). Significant difference was detected in those with fatty tissue (P = 0.002). Conclusion: DWI supported by conventional MRI data can confirm or exclude malignancy in suspicious ovarian masses. The combined analysis of quantitative and qualitative criteria and knowledge of the sequence pitfalls are required

MRI and three dimensional ultrasonography in the assessment of pulmonary hypoplasia in fetuses with urinary tract anomalies

Purpose: To analyze the correlation and agreement between three dimensional (3D) US and MRI in the assessment of pulmonary volumes of fetuses with different types of urinary tract malformations (UTM) and high-risk of pulmonary hypoplasia (PH). Patients and methods: Thirty-nine fetuses with various UTM, at risk for PH were involved in this cross-sectional study. 3D volume US data sets of the fetal lungs were acquired. The right, left and total lung volumes were calculated separately using the virtual organ computer-aided analysis (VOCAL) method with a 30° rotation. MRI of fetal lung was obtained with assessment of signal intensity and lung volumetry. Comparison between mean lung volumes was performed using unpaired t test. Agreement between the 3D-US and MRI methods was done using Cohen kappa test. Results: Good agreement was detected between the two methods (Kappa = 0.629, p = 0.001). The measured lung volumes by 3D-US were smaller than those measured by MRI (p > 0.05, non-significant). MRI showed greater specificity, PPV and diagnostic accuracy (100% each) than 3D-US (50%, 88.9% and 90% respectively). Conclusion: There is a good concordance between 3D-US and MRI in the evaluation of PH in fetuses with UTM. MRI could be reserved for borderline cases of pulmonary hypoplasia and the difficult diagnostic situations

Formulation and evaluation of sustained release paracetamol peroral matrix tablets: in vivo bioavailability evaluation in man

A comparative in vivo bioavailability evaluation of a newly formulated sustained release paracetamol peroral matrix tablets and a marketed conventional rapidly disintegrating paracetamol tablets was carried out according to a two-period, two-treatment, two-sequence, randomised crossover design with a 4-day washout period between the treatments using urinary drug excretion data. The in vivo study was conducted on 10 healthy human male volunteers aged between 24-30 years. The subjects swallowed either the sustained release or the conventional paracetamol tablets at equal dose levels and urine samples were collected at different times over a 24-hour period. Based on the urinary drug excretion data, the mean relative bioavailability of the sustained release tablets with respect to the conventional tablets was 0.949 ± 0.287, indicating that the bioavailability was not significantly different from that of the conventional tablets (P = 0.2701). Moreover, by using the sustained release tablets, it was possible to prolong the elimination half-life of the drug from 2.589 h to 3.840 h. Keywords: sustained release, paracetamol matrix tablets, comparative bioavailability, urinary drug excretion, elimination half-life Ethiopian Pharmaceutical Journal, vol. 22 (2004): 39-4

Validity of ductus arteriosus indices added to other ultrasound and Doppler parameters as markers of fetal lung maturity in pregnancy-induced hypertension

Abstract Aim of work To determine the relationship between the gestational age and the (PSV, RI and PI) of the ductus arteriosus and lung maturity and to determine the effect of pregnancy-induced hypertension on these parameters. Material and methods A prospective cohort study was carried out, in which 90 pregnant women at gestational age 34–40 weeks were selected, 50 as a control and 40 with pregnancy-induced hypertension (PIH). They underwent measurement of ductus arteriosus (DA) (PSV, RI and PI) and observing the percentage of the development of neonatal RDS in control and PIH cases. Results There was a direct correlation between the PSV, PI, RI of ductus arteriosus and development of neonatal RDS. A cutoff value for GA, PSV, RI and PI for prediction of the subsequent development of RDS was determined in control ((35.7, 89.9, 0.80, 2.14), with sensitivity (71.4, 100, 85.7, 85.7%) and specificity (93, 97.7, 97.7, 93%), respectively), and PIH (35.7, 91.1, 0.80, 2.14), with sensitivity (71.4, 100, 85.7, 100%) and specificity (71.7, 100, 85.7, 100%), respectively). Conclusions We concluded from our study that for the detection of fetal lung maturity in fetuses of GA from 34 to 40 weeks, it is better to combine GA, PSV, RI and PI of DA to detect lung maturity in control and PIH groups to get more accurate results

Data-Driven Safe Deliveries: The Synergy of IoT and Machine Learning in Shared Mobility

Shared mobility is one of the smart city applications in which traditional individually owned vehicles are transformed into shared and distributed ownership. Ensuring the safety of both drivers and riders is a fundamental requirement in shared mobility. This work aims to design and implement an adequate framework for shared mobility within the context of a smart city. The characteristics of shared mobility are identified, leading to the proposal of an effective solution for real-time data collection, tracking, and automated decisions focusing on safety. Driver and rider safety is considered by identifying dangerous driving behaviors and the prompt response to accidents. Furthermore, a trip log is recorded to identify the reasons behind the accident. A prototype implementation is presented to validate the proposed framework for a delivery service using motorbikes. The results demonstrate the scalability of the proposed design and the integration of the overall system to enhance the rider’s safety using machine learning techniques. The machine learning approach identifies dangerous driving behaviors with an accuracy of 91.59% using the decision tree approach when compared against the support vector machine and K-nearest neighbor approaches